Corrosion Behavior of 316LN and 316 Stainless Steels During Long-term Exposure to Aerated 0.5 M NaCl Using Electrochemical Noise Technique

In the present work 316LN as well as 316 stainless steel (SS) coupons each of dimensions (0.025 × 0.018 × 0.006 m³) in well-polished condition were used as two nominal electrodes which were immersed in the aerated solution of 0.5 M NaCl. Correlated current and potential electrochemical noise (EN) signals were collected at 1 Hz sampling frequency for 1 h daily over a period of 30 days. The detrended EN data were used to calculate the noise resistance (R _N) as well as the spectral noise resistance at zero frequency (R _SN^o) values and other statistical parameters. To study the nature of pits and distribution of their diameters as well as depths, extensive observations of the pitted and the blank specimens were carried out using Confocal Laser Scanning Microscopy (CLSM). The current and the potential records of the two alloys showed distinct differences in their corrosion behavior. It was observed that within less than 4 h of immersion, 316SS showed signals indicative of unstable pitting and onset of stable pitting was noticed after 48 h of exposure. However, until about 24 h, 316LN showed just the random signals and unstable pitting was observed after 28 h. The signals clearly indicated continuous growth of the stable pits in 316SS as against the repassivation of the unstable pits in 316LN after 7 days exposure. It was observed that R _N values showed a continuous decrease in the case of 316SS, but were quite stable in the case of 316LN over the exposure period. Concurrent to these observations it was observed that 316SS specimen was extensively pitted. The frequency distributions of pit diameters as well pit depths were observed to be highest at 10-20 μm and 5-10 μm, respectively. However, pits with as large as 70-80 μm diameter and as deep as 20-25 μm too were observed. No pits were observed in case of 316LN even after 30 days of exposure, an observation that corroborates well with the stable R _N values. Thus, in the present investigation, the long-term tests using EN technique coupled with CLSM studies conclusively prove that many unstable pits initiated in 316SS turn into stable ones resulting in insidious localized corrosion attack whereas the unstable pits initiated in 316LN get passivated in the simulated coastal environment.     

炭素厂的消烟除尘和噪声控制

针对炭素制品生产过程产生的粉尘、沥青烟气、噪声等主要涉及工业卫生及环境保护等方面的问题进行剖析，并对治理方法做了简要的介绍。     

汽车车内行驶噪声测试的阶次跟踪法

应用PULSE测试分析系统中阶次跟踪法,测试分析某型乘用车车内四个位置的噪声水平随发动机转速变化的关系.揭示了该型汽车在测试工况下,不同的转速对车内噪声的贡献规律.为降低车内行驶噪声和振动响应提供了重要的分析依据和参考.     

Robust sparse principal component analysis

The model for improving the robustness of sparse principal component analysis（PCA） is proposed in this paper. Instead of the l2-norm variance utilized in the conventional sparse PCA model,the proposed model maximizes the l1-norm variance,which is less sensitive to noise and outlier. To ensure sparsity,lp-norm（0 p 1） constraint,which is more general and effective than l1-norm,is considered. A simple yet efficient algorithm is developed against the proposed model. The complexity of the algorithm approximately linearly increases with both of the size and the dimensionality of the given data,which is comparable to or better than the current sparse PCA methods. The proposed algorithm is also proved to converge to a reasonable local optimum of the model. The efficiency and robustness of the algorithm is verified by a series of experiments on both synthetic and digit number image data.     

基于噪声统计模型的图像分割方法

图像分割是图像特征提取和图像识别的基础和前提,是图像研究中的热点之一.本文对目前图像分割的分类、最近几年出现的新方法、新思路以及传统图像分割中对噪声的处理进行比较简要的综述,针对噪声对图像分割的影响,提出利用噪声的统计特性建立噪声统计模型改进图像分割的新方法.     

逆M序列在机抖激光陀螺消除动态闭锁中的应用

对逆M序列在消除激光陀螺动态闭锁误差中的应用进行了研究和验证.目前多采用M序列对抖动的幅度进行调制来消除激光陀螺动态闭锁误差,而逆M序列与M序列相比不仅满足注入到激光陀螺抖动中的要求,且比M序列有其性质等方面优势.通过理论分析及M序列和逆M序列在消除机抖激光陀螺动态闭锁中实验中的应用对比,实验数据表明逆M序列在消除动态闭锁中的作用要优于M序列.     

基于改进的Capon滤波器组谱估计新方法

为了解决Capon滤波器组谱估计方法在α稳定分布噪声下性能出现退化的问题,提出了一种改进的Capon滤波器组谱估计方法,利用分数低阶协方差(FLOC)对传统的Capon滤波器组进行重构.由于分数低阶协方差的作用范围是0＜α≤2整个分数低阶空间,因此在α稳定分布噪声下其谱估计性能比基于二阶统计量方法的谱估计性能更好.计算机仿真结果显示了这种方法的优越性能,并且在高斯噪声环境下,其性能与二阶统计量下的方法类似.     

一种气象卫星数据脉冲噪声滤除方法

气象卫星数据在采集或者传输的过程中,往往会引入不同程度的脉冲噪声。为提高图像质量,滤除噪音,进行可信度分析,提出了一种三阶段气象卫星数据脉冲噪声检测和滤除方法。在算法第一阶段,利用均值与均方差比值差值序列建立排序检测器(ROD),检测出图像中所有可能的脉冲噪声点;第二阶段,采用逐点滑动N×N窗口,按照每个可能的脉冲噪声点在不同的滑动窗口被重复检测到的次数,建立噪声可信度。第三阶段,对高噪声点进行滤波;对低噪声点迭代排序检测,如果可识别有噪声点,再进行滤波。结果表明,算法可以准确检测和滤除脉冲噪声,并保持数据中非噪声点信息。     

基于最小二乘法的HDR图像快速滤噪算法

提出一种针对高动态范围（HDR）图像滤噪的新方法,通过对用于合成HDR的一组图像进行滤噪来实现。在亮度空间中,通过求解加权最小二乘问题拟合L-t直线,并用该直线修正亮度值,从而到达滤噪目的。实验表明该算法运算量小,能有效去除椒盐型噪声,对高斯型噪声抑制效果明显,优于A.&E.(Ahmet&Erit)的加权求和滤噪算法。